A decision tree can assist in exploring conditional probabilities among several possible actions and outcomes (see Fig. D13). It starts out at the left square and connects to new decisions (squares) or uncertainties (circle), which are also called nodes. On the connecting lines (edges) the estimated probabilities can be represented. One may use a large number of branches if necessary. Each probability can be multiplied by a numerical value (percentage or fraction) and at the end the most rewarding or harmful decision can be evaluated. Such a procedure has merits in business or in medicine when different treatments are contemplated. Several software tools are available on the Internet. (Chen HY et al 2007 New England J Med 356:11)
